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+# MS3111 Data Analytics with Excel VBA
+
+## Proposal
+
+## Team Member:
+
+- Fung Sum Yu 57158594
+- Chiu Cheung Sin 56700379
+- Cheung Chun Hei 57141700
+- Ma Pui Man 57302260
+
+## Background and Source data
+
+AB Insurance Ltd is a newly established company in 2020.
+In order to analyse the insurance sales situation and evaluate the agents' working performance, the company decided to record every transaction daily and update it yearly. There are 3 source workbooks with different purpose:
+
+1. **Product sales workbook** [Product_Sales.xlsx](../src/xlsx/Product_Sales.xlsx)
+
+Column:
+
+- Sales No. `PRODUCT_SALES_SALES_NO_COL`
+- Date `PRODUCT_SALES_DATE_COL`
+- Product Category `PRODUCT_SALES_PRODUCT_CATEGORY_COL`
+- Selling Unit `PRODUCT_SALES_SELLING_UNIT_COL`
+- Selling Price `PRODUCT_SALES_SELLING_PRICE_COL`
+
+It mainly records what kind of products have been sold in 2023 with the detailed date, selling unit and selling price. There is a total of 200 invoices, followed by the Sales Number.
+
+![](./images/Picture1.png)
+
+1. **Agent Sales workbook** [Agent_Sales.xlsx](../src/xlsx/Agent_Sales.xlsx)
+
+   Column:
+
+   - Sales No. `AGENT_SALES_SALES_NO_COL`
+   - Date `AGENT_SALES_DATE_COL`
+   - Agent Name `AGENT_SALES_AGENT_NAME_COL`
+   - Team `AGENT_SALES_TEAM_COL`
+   - Selling Price `AGENT_SALES_SELLING_PRICE_COL`
+   - Commision(%) `AGENT_SALES_COMMISION_PCT_COL`
+
+   Here are the company's two groups of insurance agents in 2023 sales records, a total of two groups divided into A team and B team. Each group have 5 members, and we have a total of 10 agents. They are Alex, Ben, Candy, Danny, and Eason from the A team and Filex, Gary,Henry, Irene, and Jenny from the B team. The company keep a detailed record of each transaction’s date, agent name, team, selling price and commission rate, respectively.
+
+   ![](./images/Picture2.png)
+
+   Different commission rates for different product types:
+
+   - Life insurance (30%)
+   - Accident insurance (25%)
+   - Health insurance (20%)
+   - Travel insurance (35%)
+   - Vehicle insurance (15%)
+
+2. **Agent working performance workbook** [Agent_Working_Performance.xlsx](../src/xlsx/Agent_Working_Performance.xlsx)
+
+   Column:
+
+   - Date `AGENT_WORKING_PERFORMANCE_DATE_COL`
+   - Name `AGENT_WORKING_PERFORMANCE_NAME_COL`
+   - Team `AGENT_WORKING_PERFORMANCE_TEAM_COL`
+   - No. of New Case `AGENT_WORKING_PERFORMANCE_NO_OF_NEW_CASE_COL`
+   - No. of Collapsed Case `AGENT_WORKING_PERFORMANCE_NO_OF_COLLAPSED_CASE_COL`
+
+   As an insurance company, in addition to finding new business opportunities, ensuring that our customers continue to purchase our old policies is also an important indicator of how well our agent is doing. Hence, this workbook records the number of new cases set up, and the number of old policed collapsed in 2023. In case to evaluate the agent working, the data record follows the date, agent name, agent’s team and the specific number of new and collapsed cases.
+
+   ![](./images/Picture3.png)
+   ![](./images/Picture4.png)
+
+## Data Manipulation:
+
+A new Excel workbook called 'Analysis Workbook' is created to store manipulated data. In the `Combined Data` worksheet, relevant data will be extracted from the three source data workbooks mentioned in the previous section, with those duplicate entries or columns removed.
+
+Column:
+
+- Date `ANALYSIS_WORKBOOK_COMBINED_DATA_DATE_COL`
+- Sales No. `ANALYSIS_WORKBOOK_COMBINED_DATA_SALES_NO_COL`
+- Month `ANALYSIS_WORKBOOK_COMBINED_DATA_MONTH_COL`
+- Quater `ANALYSIS_WORKBOOK_COMBINED_DATA_QUATER_COL`
+- Agent Name `ANALYSIS_WORKBOOK_COMBINED_DATA_AGENT_NAME_COL`
+- Team `ANALYSIS_WORKBOOK_COMBINED_DATA_TEAM_COL`
+- Product Category `ANALYSIS_WORKBOOK_COMBINED_DATA_PRODUCT_CATEGORY_COL`
+- Selling Price `ANALYSIS_WORKBOOK_COMBINED_DATA_SELLING_PRICE_COL`
+- Commision(%) `ANALYSIS_WORKBOOK_COMBINED_DATA_COMMISION_PCT_COL`
+- Selling Unit `ANALYSIS_WORKBOOK_COMBINED_DATA_SELLING_UNIT_COL`
+- Commision($) `ANALYSIS_WORKBOOK_COMBINED_DATA_COMMISION_HKD_COL`
+- Rank `ANALYSIS_WORKBOOK_COMBINED_DATA_RANK_COL`
+- Bonus `ANALYSIS_WORKBOOK_COMBINED_DATA_BONUS_COL`
+- Total commission `ANALYSIS_WORKBOOK_COMBINED_DATA_TOTAL_COMMISSION_COL`
+- No. of Collapsed case `ANALYSIS_WORKBOOK_COMBINED_DATA_NO_OF_COLLAPSED_CASE_COL`
+- Margin `ANALYSIS_WORKBOOK_COMBINED_DATA_MARGIN_COL`
+
+![](./images/Picture5.png)
+
+For further analysis, some columns are newly expended and computed.
+
+### Drill down to Month and Quarter
+
+The 'Month'(`ANALYSIS_WORKBOOK_COMBINED_DATA_MONTH_COL`) and 'Quarter'(`ANALYSIS_WORKBOOK_COMBINED_DATA_QUATER_COL`) columns display the month and quarter of the insurance transaction, respectively, according to the data in the 'Date'(`ANALYSIS_WORKBOOK_COMBINED_DATA_DATE_COL`) column.
+
+![](./images/Picture6.png)
+
+### Calculate every comission
+
+As a different commission rate is assigned to each product category, a column named 'Commission($)'(`ANALYSIS_WORKBOOK_COMBINED_DATA_COMMISION_PCT_COL`) is computed to show how much the representing agent could gain from the transaction. The amount is calculated by multiplying the selling price, selling unit, and the commission rate, referred to as `=H2*J2*I2` in Excel.
+
+![](./images/Picture7.png)
+
+### Sum up each sales agent insurance sales per month
+
+Each sales agent is assigned a monthly sales performance ranking by summing up each sales agent's calculated insurance sales per month (more details are provided in the next section). The ' Rank ' column shows each month's top 3 sales agents. The top 3 sales agents will receive bonuses of 1,000, 500, and 100, respectively, displayed in the "Bonus" column.
+
+![](./images/Picture8.png)
+
+### Calculate `total comission`
+
+The 'Total commission' column is the sum of the sales commission and the bonus added. In Excel, `=K2+M2`.
+
+![](./images/Picture9.png)
+
+### Calculate `margin`
+
+The 'Margin' column shows the overall margin of each transaction, computed by subtracting the total commission from the selling price. In Excel, ‘=H2-N2’.
+
+![](./images/Picture10.png)
+
+## Analysis Workbook & Report Workbook:
+
+### 1. Sales Analysis (Monthly and Quarterly) worksheet
+
+`SALES_ANALYSIS_MONTHLY_AND_QUARTERLY_SHEET`
+
+![](./images/Picture11.png)
+
+There are different columns for different datasets. Month and Quarter columns represent the timeslot of the sales. The product category column represents the types of insurance sold on the period of time. We have used the “sum if” function in excel to generate the selling unit for the total number of every month. The selling unit times the selling price of the product will equal the column of Monthly sales. We used the “sum” function in excel to generate a Quarterly sales column by adding up the data of Monthly sales for every four months. Moreover, the “commission” column of the workbook has used the “sum if” function to generate the data from the Combine Data worksheet. The Quarterly Commission columns are produced by using the “sum” function of Excel to add up the commission for every four months. Finally, we have the column of monthly margin and quarterly margin respectively. It calculates the difference between monthly sales and the commission and minus the fixed cost $1600.
+
+The Sales Analysis (Monthly and Quarterly) contains crucial data pertaining to the sales performance of insurance products over specific time periods. The Month and Quarter columns provide a breakdown of sales figures on a monthly and quarterly basis, allowing for detailed analysis of sales trends and patterns. The Product Category column categorizes the different types of insurance products sold, offering insights into the demand and popularity of each category. The utilization of the "sum if" function in Excel to calculate selling units and monthly sales enables a comprehensive overview of the volume and revenue generated from each product category.
+
+Moreover, the Commission column in the workbook reflects the commissions earned by sales representatives for selling insurance products, drawing data from the Combine Data Worksheet to ensure accuracy and consistency. This commission data is aggregated into the Quarterly Commission column, providing visibility into the earnings of sales personnel over a quarterly time frame.
+
+Furthermore, the Monthly Margin and Quarterly Margin columns play a critical role in determining the profitability of the sales operations. By subtracting the total commission and fixed costs from the monthly and quarterly sales figures, these metrics offer valuable insights into the financial performance and efficiency of the sales activities. The comprehensive data presented in this workbook serves as a valuable tool for assessing sales performance, identifying opportunities for growth, and making informed business decisions.
+
+Figures 1 (a) and 1(b) in the Report Workbook present a visual representation of the monthly sales and commissions for the year 2023. The line graphs in both figures exhibit a strikingly similar pattern, suggesting a direct relationship between sales and commissions. This correlation indicates that as sales increase or decrease, there is a corresponding impact on the commission earned by sales representatives. The alignment in the shape of the sales and commission lines signifies a consistent and proportional change between these two variables over the course of the year.
+
+This direct variation relationship between sales and commissions has significant implications for the financial performance of the business. The interplay between these two critical metrics not only influences revenue generation but also affects the overall profitability and margin of the company. Figure 3 further illustrates the impact of this relationship on the monthly margin, which is calculated as the difference between sales, commission, and the fixed cost of $1600.
+
+The observed fluctuations in the monthly margin can be attributed to the dynamic nature of sales and commission figures. Changes in sales volume, commission rates, or operating expenses can directly influence the monthly margin, shaping the financial health and viability of the business. These fluctuations may provide valuable insights into the efficiency of sales operations, the effectiveness of commission structures, and the overall cost management strategies employed by the company.
+
+Based on the direct variation relationship between sales and commissions showcased in Figures 1 and 2, one hypothesis could suggest that a strategic increase in sales efforts could lead to a corresponding rise in commission earnings, contributing to improved profitability. Conversely, a decline in sales performance may result in lower commission income, potentially leading to tighter profit margins. These findings underscore the intricate interplay between sales, commissions, and margins in shaping the financial performance of the business.
+
+| Figure 1(a)                 | Figure 1(b)                 |
+| --------------------------- | --------------------------- |
+| ![](./images/Picture12.png) | ![](./images/Picture13.png) |
+
+| Figure 2:                   |
+| --------------------------- |
+| ![](./images/Picture14.png) |
+
+| Figure 3:                   |
+| --------------------------- |
+| ![](./images/Picture15.png) |
+
+### 2. Sales Analysis (Product Category) worksheet
+
+![](./images/Picture16.png)
+
+![](./images/Picture17.png)
+
+The worksheet is to provide a comprehensive overview of sales performance for different types of insurance products on a monthly basis. By utilizing the "sum if" function in Excel, the workbook accurately calculates the sales amount and sales unit for each type of insurance, including Travel insurance, Health insurance, Life insurance, Vehicle insurance, and Accident insurance.
+
+The Sales Amount column displays the total sales amount for each type of insurance product for a specific month, allowing for a clear comparison between different product categories. This data can be used to track sales trends, monitor performance, and identify areas for improvement in sales strategies.
+
+Similarly, the Sales Unit column showcases the total number of cases or transactions completed for each type of insurance product within a month. This information is valuable for understanding customer demand, evaluating business growth, and making informed decisions on resource allocation.
+
+To sum up, the Sales Analysis (Product Category) serves as a valuable tool for analyzing sales performance, identifying key trends, and making strategic decisions to drive business success in the insurance industry.
+
+Figures 4 and 5 in Report Workbook depict the sales amount and sales unit data for a distinct month, presenting a visual representation of the distribution of sales among various types of insurance products. Through the utilization of pie charts, the data is effectively segmented to
+display the relative percentages of each insurance category, enabling a straightforward comparative analysis between the different types. By visually illustrating the proportions of sales attributed to each type of insurance, stakeholders are provided with a simplified and easily interpretable overview of the sales distribution. This graphical representation facilitates a comprehensive assessment of the variations in sales performance across the diverse insurance categories, offering valuable insights into the comparative success and contribution of each product type to the overall sales volume and number of units sold. The use of pie charts in presenting the sales amount and sales unit data serves to streamline the analysis process, enabling stakeholders to swiftly discern the relative performance of different insurance categories and make well-informed decisions based on the distribution of sales in the depicted month.
+
+| Figure 4                    | Figure 5                    |
+| --------------------------- | --------------------------- |
+| ![](./images/Picture18.png) | ![](./images/Picture19.png) |
+
+### 3.Agent performance analysis (Commission) worksheet
+
+![](./images/Picture20.png)
+
+From this worksheet, we can generate charts like Figures 6 and 7 in Report Workbook which depict the total sales commission for Team A and Team B for a distinct month. Figure 8 depicts the top 5 sales agents for a distinct month. Analyzing performance helps determine whether the existing commission structure effectively incentivizes agents to achieve organizational goals. Commission analysis helps evaluate the performance of individual agents. This evaluation is crucial for providing feedback, setting performance targets, and making decisions regarding promotions or changes in responsibilities. Each bar might represent an individual agent, and the height of the bar could represent.
+
+various performance indicators We have used the “sum if” function in Excel to generate the commission for the total number of every month and find out the top 5 agents in each month.
+
+| Figure 6                    | Figure 7                    |
+| --------------------------- | --------------------------- |
+| ![](./images/Picture21.png) | ![](./images/Picture22.png) |
+
+Figure 8:
+
+![](./images/Picture23.png)
+
+### 4.Case Persistency Worksheet
+
+![](./images/Picture24.png)
+
+The Case Persistency column is a new computation with equation "(No. of New Case – No. of collapsed case) / (No. of New Case + No. of collapsed case)". Figure 9 and Figure 10 depict the case distribution among the new cases and collapse. Through the utilization of pie charts, the data is effectively segmented to display the relative percentages of each team.
+
+In the context of insurance, the concepts of case distribution, new cases, collapse, and the use of bar charts for agent performance visualization can be applied in various ways to enhance efficiency, track workload, and provide insights.
+
+| Figure 9                    | Figure 10                   |
+| --------------------------- | --------------------------- |
+| ![](./images/Picture25.png) | ![](./images/Picture26.png) |